Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
4,753
datasets available to search
ShareScore release 0.9.0
Dataset results
4,753 results for “SHAPE”
Combined influence of intrinsic and environmental factors in shaping productivity in a small pelagic gull, the black-legged kittiwake Rissa tridactyla
Open the record for dataset details and reuse information.
Data from: Biogeography and anthropogenic impact shape the success of invasive wasps on New Zealand’s offshore islands
Open the record for dataset details and reuse information.
Plant traits shape soil legacy effects on individual plant-insect interactions
Open the record for dataset details and reuse information.
Data from: Inbreeding shapes the evolution of marine invertebrates
Open the record for dataset details and reuse information.
Sampling biases shape our view of the natural world
Open the record for dataset details and reuse information.
Data from: Physical and social cues shape nest-site preference and prey capture behavior in social spiders
Open the record for dataset details and reuse information.
Habitat use, interspecific competition, and phylogenetic history shape the evolution of claw and toepad morphology in Lesser Antillean anoles
Open the record for dataset details and reuse information.
Shape-controlled single-crystal growth of InP at low temperatures down to 220 ℃
Open the record for dataset details and reuse information.
Fig. 3 in Plasticity in the shape and growth pattern of asteriscus otolith of black prochilodus Prochilodus nigricans (Teleostei: Characiformes: Prochilodontidae) freshwater Neotropical migratory fish
Fig. 3. Cluster analysis based on the euclidean distances of the wavelet functions by shape analysis of asteriscus otoliths Prochilodus nigricans between rivers. S (Solimões); J (Japurá) and N (Negro).
Fig. 2 in Plasticity in the shape and growth pattern of asteriscus otolith of black prochilodus Prochilodus nigricans (Teleostei: Characiformes: Prochilodontidae) freshwater Neotropical migratory fish
Fig. 2. Canonical variate analysis of the first 5 PC compo- nents and fish length data of the Prochilodus nigricans for all localities, with 95% confidence. Solimões (blue); Japurá (red) and Negro (green).
Fig. 4 in Diet and body shape among populations of Bryconamericus iheringii (Otophysi: Characidae) across the Campos Sulinos ecosystem
Fig. 4. Partial least squares canonical analysis depicting the covariation between: a. dietary (blue) and environmental (brown) variables; b. morphological (orange) and environmental (brown) variables; c. dietary (blue) and morphological variables (orange). Variables near the edge of the circle are better represented by the model. Variables near one another are positively correlated, whereas variables opposite one another are negatively correlated. Uncorrelated variables are orthogonal.
Fig. 3 in Diet and body shape among populations of Bryconamericus iheringii (Otophysi: Characidae) across the Campos Sulinos ecosystem
Fig. 3. Relative warps (RW) of body shapes among 22 populations of Bryconamericus iheringii: Alegrete (AL), Jaguarão (JG), Santo Antônio das Missões (SM), São Gabriel (SG), Santiago (ST), São Pedro do Sul (SS), Soledade (SL), Quaraí (QR), Santana da Boa Vista (SV) and Lavras do Sul (LV). Warp transformation grids depict the body shapes associated with the extremes of each axis.
Fig. 2 in Diet and body shape among populations of Bryconamericus iheringii (Otophysi: Characidae) across the Campos Sulinos ecosystem
Fig. 2. Individual of Bryconamericus iheringii (UFRGS 21339) with the landmarks used for geometric morphometric. 1 = Tip of snout; 2 = Top of head (at the supraoccipital bone); 3 = Anterior insertion of dorsal fin; 4 = Posterior insertion of dorsal fin; 5 = Posterior insertion of adipose fin; 6 = Dorsal end of caudal peduncle; 7 = Ventral end of caudal peduncle; 8 = Posterior insertion of anal fin; 9 = Anterior insertion of anal fin; 10 = Origin of pelvic fin; 11 = Origin of pectoral fin; 12 = Ventral end of head; 13 = Tip of the upper jaw (maxillary bone); 14 = Anterior margin of eye; 15 = Posterior margin of eye; 16 = Anterior margin of opercule.
Fig. 1 in Diet and body shape among populations of Bryconamericus iheringii (Otophysi: Characidae) across the Campos Sulinos ecosystem
Fig. 1. Location of the ten municipalities in the Rio Grande do Sul State (RS), Brazil, and main land coverage. The landcover map was make with software ArcGIS 10.2 (ESRI, 2013) using the database of Pampa Biome cover of 2009 (UFRGS, 2016).
The role of the Arp2/3 complex in shaping the dynamics and structures of branched actomyosin networks
<p>Actomyosin networks give cells the ability to move and divide. These networks contract and expand while being driven by active energy-consuming processes such as motor protein walking and actin polymerization. Actin dynamics is also regulated by actin-binding proteins, such as the actin-related protein 2/3 (Arp2/3) complex. This complex generates branched filaments thereby changing the overall organization of the network. In this work, the spatiotemporal patterns of dynamical actin assembly accompanying the branching-induced reorganization caused by Arp2/3 were studied using a computational model (MEDYAN); this model simulates actomyosin network dynamics as a result of chemical reactions whose rates are modulated by rapid mechanical equilibration. We show that branched actomyosin networks relax significantly more slowly than do unbranched networks. Also, branched networks undergo rare convulsive movements, “avalanches”, that release strain in the network. These avalanches are associated with the more heterogeneous distribution of mechanically-linked filaments displayed by branched networks. These far-from equilibrium events arising from the marginal stability of growing actomyosin networks provide a possible mechanism of the “cytoquakes” recently seen in experiments.</p>
METHODS. Bovine ilia were used in the simulations because their histological structure (a fibrolamellar cortex overlying cancellous bone26) was found to match that of the Triceratops ilium. Bone sections 10 x 50 x 縠 3.0 cm with cortices ranging from 0.5 to 5.5 mm in depth (the range of initial cortical-thickness estimates based on gross morphology) were mounted on a servohydraulic mechanical loading frame (MTS Bionix, Minneapolis) and penetrated with an aluminium-bronze T. rex tooth replica. The replica was cast from an actual adult T. rex maxillary tooth, after casts made from some ofthe deeper bite marks revealed the size and shape of the teeth that had impacted the pelvis8 • The replica was penetrated into the ilia sections at 1 mm s-1 to a depth of 11.5 mm, equivalent to the maximum depth of the deepest ilium bite mark8 • Forces were measured with an MTS 25 N strain-gauge-based axial load cell accurate to 0.2%. The forces increased with increasing penetration depth even after the cortical layer had been perforated and the underlying cancellous bone was being crushed. The increase in force with penetration depth is attributed to a greater cortical surface area coming into contact with the semi-conical penetrator tooth as it descended through the ilia. in Bite-force estimation for Tyrannosaurus rex from tooth-marked bones
METHODS. Bovine ilia were used in the simulations because their histological structure (a fibrolamellar cortex overlying cancellous bone26) was found to match that of the Triceratops ilium. Bone sections 10 x 50 x 縠 3.0 cm with cortices ranging from 0.5 to 5.5 mm in depth (the range of initial cortical-thickness estimates based on gross morphology) were mounted on a servohydraulic mechanical loading frame (MTS Bionix, Minneapolis) and penetrated with an aluminium-bronze T. rex tooth replica. The replica was cast from an actual adult T. rex maxillary tooth, after casts made from some ofthe deeper bite marks revealed the size and shape of the teeth that had impacted the pelvis8 • The replica was penetrated into the ilia sections at 1 mm s-1 to a depth of 11.5 mm, equivalent to the maximum depth of the deepest ilium bite mark8 • Forces were measured with an MTS 25 N strain-gauge-based axial load cell accurate to 0.2%. The forces increased with increasing penetration depth even after the cortical layer had been perforated and the underlying cancellous bone was being crushed. The increase in force with penetration depth is attributed to a greater cortical surface area coming into contact with the semi-conical penetrator tooth as it descended through the ilia.
Data associated with "Adjoint methods for stellarator shape optimization and sensitivity analysis"
<p>All data produced for this dissertation and the associated post-processing scripts have been archived. </p>
Classification and Quantification of Strawberry Fruit Shape
<p>"Classification and Quantification of Strawberry Fruit Shape" is a dataset that includes raw RGB images and binary images of strawberry fruit. These folders contain JPEG images taken from the same experimental units on 2 different harvest dates. Images in each folder are labeled according to the 4 digit plot ID from the field experiment (####_) and the 10 digit individual ID (_##########).</p> <p><strong>"H1"</strong> and<strong> "H2"</strong> folders contain RGB images of multiple fruits. Each fruit was extracted and binarized to become the images in "H1_indiv" and "H2_indiv".</p> <p><strong>"H1_indiv"</strong> and<strong> "H2_indiv"</strong> folders contain images of individual fruit. Each fruit is bordered by ten white pixels. There are a total of 6,874 images between these two folders. The images were used then resized and scaled to be the images in "ReSized".</p> <p><strong>"ReSized"</strong> contains 6,874 binary images of individual berries. These images are all square images (1000x1000px) with the object represented by black pixels (0) and background represented with white pixels (1). Each image was scaled so that it would take up the maximum number of pixels in a 1000 x 1000px image and would maintain the aspect ratio.</p> <p><strong>"Fruit_image_data.csv"</strong> contains all of the morphometric features extracted from individual images including intermediate values.</p> <p>All images title with the form "B##_NA" were discarded prior to any analyses. These images come from the buffer plots, not the experimental units of the study.</p> <p><strong>"PPKC_Figures.zip" </strong>contains all figures (F1-F7) and supplemental figures (S1-S7_ from the manuscript. Captions for the main figures are found in the manuscript. Captions for Supplemental figures are below.</p> <p>Fig. S1 Results of PPKC against original cluster assignments. Ordered centroids from k = 2 to k = 8. On the left are the unordered assignments from k-means, and the on the right are the order assignments following PPKC. Cluster position indicated on the right [1, 8].</p> <p>Fig. S2 Optimal Value of k. (A) Total within clusters sum of squares. (B) The inverse of the Adjusted R . (C) Akaike information criterion (AIC). (D) Bayesian information criterion (AIC). All metrics were calculated on a random sample of 3, 437 images (50%). 10 samples were randomly drawn. The vertical dashed line in each plot represents the optimal value of k. Reported metrics are standardized to be between [0, 1].</p> <p>Fig. S3 Hierarchical clustering and distance between classes on PC1. The relationship between clusters at each value of k is represented as both a dendrogram and as bar plot. The labels on the dendrogram (i.e., V1, V2, V3,..., V10) represent the original cluster assignment from k-means. The barplot to the right of each dendrogram depicts the elements of the eigenvector associated with the largest eigenvalue form PPKC. The labels above each line represent the original cluster assignment.</p> <p>Fig. S4 BLUPs for 13 selected features. For each plot, the X-axis is the index and the Y-axis is the BLUP value estimated from a linear mixed model. Grey points represent the mean feature value for each individual. Each point is the BLUP for a single genotype.</p> <p>Fig. S5 Effects of Eigenfruit, Vertical Biomass, and Horizontal Biomass Analyses. (A) Effects of PC [1, 7] from the Eigenfruit analysis on the mean shape (center column). The left column is the mean shape minus 1.5× the standard deviation. Right is the mean shape plus 1.5× the standard deviation. The horizontal axis is the horizontal pixel position. The vertical axis is the vertical pixel position. (B) Effects of PC [1, 3] from the Horizontal Biomass analysis on the mean shape (center column). The left column is the mean shape minus 1.5× the standard deviation. Right is the mean shape plus 1.5× the standard deviation. The horizontal axis is the vertical position from the image (height). The vertical axis is the number of activated pixels (RowSum) at the given vertical position. (C) Effects of PC [1, 3] from the Vertical Biomass analysis on the mean shape (center column). The left column is the mean shape minus 1.5× the standard deviation. Right is the mean shape plus 1.5× the standard deviation. The horizontal axis is the horizontal position from the image (width). The vertical axis is the number of activated pixels (ColSum) at the given horizontal position.</p> <p>Fig. S6 PPKC with variable sample size. Ordered centroids from k = 2 to k = 5 using different image sets for clustering. For all k = [2, 5], k-means clustering was performed using either 100, 80, 50%, or 20% of the total number of images; 6,874, 5, 500, 3, 437, and 1, 374 respectively. Cluster position indicated on the right [1, 5].</p> <p>Fig. S7 Comparison of scale and continuous features. (A.) PPKC 4-unit ordinal scale. (B.) Distributions of the selected features with each level of k = 4 from the PPKC 4-unit ordinal scale. The light gray line is cluster 1, the medium gray line is cluster 2, the dark gray line is cluster 3, and the black line is cluster 4.</p>
Fig. 5 in The first fossil wedge-shaped beetle (Coleoptera, Ripiphoridae) from the middle Jurassic of China
Fig. 5. An extant species of Ptilophorinae, Trigonodera tokejii (Nomura & Nakane, 1959). A. Habitus, dorsal view. B. Habitus, lateral view. C. Head, frontal view. D. Antenna. Scale bars: A–B = 5.0 mm; C–D = 1.0 mm.
Data from: Cross-sex genetic covariances limit the evolvability of wing-shape within and among species of Drosophila
The independent evolution of males and females is potentially constrained by both sexes inheriting the same alleles from their parents. This genetic constraint can limit the evolvability of complex traits; however, there are few studies of multivariate evolution that incorporate cross-sex genetic covariances in their predictions. Drosophila wing-shape has emerged as a model high-dimensional phenotype; wing-shape is highly evolvable in contemporary populations, and yet perplexingly stable across phylogenetic timescales. Here we show that cross-sex covariances in D. melanogaster, given by the B-matrix, may considerably bias wing-shape evolution. Using random skewers, we show that B would constrain the response to antagonistic selection by 90%, but would double the response to concordant selection. Both cross-sex within-trait and cross-sex cross-trait covariances determined the response to antagonistic selection, but only cross-sex within-trait covariances facilitated the response to concordant selection. Similar patterns were observed when selection was applied in the direction of extant sexual dimorphism in D. melanogaster, and in directions of most and least dimorphic variation across the Drosophila phylogeny. Our results highlight the importance of considering between-sex genetic covariances when making predictions about evolution on both macro- and micro- evolutionary timescales, and may provide one more explanatory piece in the puzzle of stasis.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.